Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network

Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.     

SCAP: a new methodology for safety management based on feedback from credible accident-probabilistic fault tree analysis system

As it is conventionally done, strategies for incorporating accident--prevention measures in any hazardous chemical process industry are developed on the basis of input from risk assessment. However, the two steps-- risk assessment and hazard reduction (or safety) measures--are not linked interactively in the existing methodologies. This prevents a quantitative assessment of the impacts of safety measures on risk control.We have made an attempt to develop a methodology in which risk assessment steps are interactively linked with implementation of safety measures. The resultant system tells us the extent of reduction of risk by each successive safety measure. It also tells based on sophisticated maximum credible accident analysis (MCAA) and probabilistic fault tree analysis (PFTA) whether a given unit can ever be made 'safe'. The application of the methodology has been illustrated with a case study.     

Opportunities and Challenges of Artificial Intelligence for Green Manufacturing in the Process Industry

Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.     

Developing a risk/cost framework for routing truck movements of hazardous materials

As the United States continues to increase its dependence on industrial technologies which require hazardous materials and generate hazardous wastes, concern is mounting over the safe transport of hazardous cargo. It is estimated that 1.5 billion tons of hazardous cargo are moved through the nation's transportation systems (excluding pipeline), with truck as the primary mode of transport. Because of the dynamic nature of exposure to the population and environment associated with the transport of hazardous cargo, it is important to develop an accurate representation of this type of transport risk, and to structure a framework for designating a permanent set of shipping routes based on optimizing across risks and costs. This paper describes a methodology which has been developed that incorporates risk and cost into a framework for optimizing the routing of truck movements of hazardous materials. Considerable attention is focused on the risk estimation part of this process, as this is a subject of much uncertainty and of considerable significance to policymakers. The resulting methodology is applied in a regional setting to illustrate its use as an analysis tool. Enhancements to the model structure and extensions beyond the truck routing problem are also discussed.     

Integrated risk analysis for acute and chronic exposure to toxic chemicals

The traditional practice to assess and evaluate different types of risk in isolation to each other are liable to give erroneous results. Integrated risk assessment is an answer to overcome this problem. This paper presents the cumulative or integrated assessment of acute risk posed by accidental release of hazardous chemical (e.g. chlorine) and chronic risk induced by toxic chemicals (e.g. cadmium, chromium and nickel) present in the ambient environment. The present study has been carried out in a most simplified way to demonstrate and appreciate the broader context of integrated risk analysis (IRA). It has been observed that the inclusion of background risk factors (BRF) in individual risk factors (IRF) related to an industry may significantly alter the siting and planning strategies of that industry.     

Risk analysis of corrosion failures of equipment in refining and petrochemical plants based on fuzzy set theory

Corrosion failures of process equipment have been one of the main sources of risk to refining and petrochemical plants. For reducing failure risk levels and optimizing inspection plans, risk analysis of equipment failures resulting from corrosion need to be implemented. However, due to the complexity and uncertainty of the refining and petrochemical units and risks, effective analyses are hard to accomplish by using conventional risk techniques. With respect to this, a new model for risk analysis of corrosion failures of equipment is developed base on fuzzy set theory. In this model, two essential parts of failure risk (i.e., failure likelihood and severity of failure consequence) are first estimated by using fuzzy synthetic evaluation, and then integrated into a risk index by fuzzy risk graph which is established based on fuzzy logic system. In order to demonstrate the feasibility of this model, an application example in an overhead system of a crude-oil distillation unit was presented. The results show that this model is effective and feasible.     

Bayesian Belief Network Used in the Chemical and Process Industry: A Review and Application

With the increasing growth of the chemical and process industries, it is necessary to ensure the safe operation of their complex and often hazardous installations, given their proximity to residential areas. Several techniques, such as fault tree analysis (FTA), bow-tie analysis (BTA), and Bayesian belief networks (BBNs), have been developed for adequate probabilistic risk assessment and management. The current work is aimed at performing a brief statistical review of the use of Bayesian networks in the chemical and process industry within the last decade. The review reveals that Bayesian networks have been used extensively in various forms of safety and risk assessment. This trend is attributable to the complexity of the installations found in this industry and the ability of BBN to intuitively represent these complexities, handle uncertainties, and update event probabilities. The paper is concluded with an illustrative example of the use of BBN to investigate the effectiveness of the safety barriers of a gas facility.

     

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors, misinterpretation, and miscommunication of requirements and decision-making processes play their roles in software success forecasting. We discussed a potential relationship between forecasting of software success or failure and the development processes. We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study, and they were more likely to rate software success forecasting linking to the development processes. Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate. The results of this empirical study also validated that requirements’ misinterpretation and miscommunication were the main causes behind software systems’ failure. It has been seen that reliable, relevant, and trustworthy sources of information help in decision-making to predict software systems’ success in the software industry. This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects. Future investigation can be performed to identify the other human factors that may impact software systems’ success.     

Hazardous materials transportation: a risk-analysis-based routing methodology

This paper introduces a new methodology based on risk analysis for the selection of the best route for the transport of a hazardous substance. In order to perform this optimisation, the network is considered as a graph composed by nodes and arcs; each arc is assigned a cost per unit vehicle travelling on it and a vehicle capacity. After short discussion about risk measures suitable for linear risk sources, the arc capacities are introduced by comparison between the societal and individual risk measures of each arc with hazardous materials transportation risk criteria; then arc costs are defined in order to take into account both transportation out-of-pocket expenses and risk-related costs. The optimisation problem can thus be formulated as a 'minimum cost flow problem', which consists of determining for a specific hazardous substance the cheapest flow distribution, honouring the arc capacities, from the origin nodes to the destination nodes. The main features of the optimisation procedure, implemented on the computer code OPTIPATH, are presented. Test results about shipments of ammonia are discussed and finally further research developments are proposed.     

A risk management initiative implemented in Canada

This paper describes recent initiatives in Canada that lead to a new regulation on environmental emergencies under the Canadian Environmental Protection Act of 1999. The regulation includes a list of hazardous substances with threshold quantities. It has requirements for prevention, preparedness, response and recovery. The regulation is based on voluntary guidelines developed by industry, public authorities, municipalities and representatives of the public. The guidelines are a reference for industry and municipalities to help them manage risk related to major industrial accidents. The guidelines released in July 2002 are innovative in the sense that municipalities are strongly involved in the risk management process through the creation of Local Emergency Planning Committees (Joint Committees) with representatives from industry, municipalities and public. This work appears as a relevant approach to involve the public in the decision-making process and makes people aware of the hazards and the measures taken to control risk.     

Database development and uncertainty treatment for estimating pipe failure rates and rupture frequencies

Estimates of failure rates for nuclear power plant piping systems are important inputs to Probabilistic Risk Assessments (PRA) and risk informed applications of PRA. Such estimates are needed for initiating event frequencies for Loss of Coolant Accidents and internal flooding events and for risk informed evaluations of piping system in-service inspection programs. A critical issue in the estimation of these parameters is the treatment of uncertainties, which can exceed an order of magnitude deviation from failure rate point estimates. Sources of uncertainty include failure data reporting issues, scarcity of data, poorly characterized component populations, and uncertainties about the physical characteristics of the failure mechanisms and root causes. A methodology for quantifying these uncertainties using a Bayes' uncertainty analysis method was developed for the EPRI risk informed in-service inspection program and significantly enhanced in subsequent applications. In parallel with these efforts, progress has been made in the development of pipe failure databases that contain the quantity and quality of information needed to support piping system reliability evaluations. Examples are used in this paper to identify technical issues with previous published estimates of pipe failure rates and the numerical impacts of these issues on the pipe failure rates and rupture frequencies are quantified.     

Making the business case for process safety using value-at-risk concepts

An increasing emphasis on chemical process safety over the last two decades has led to the development and application of powerful risk assessment tools. Hazard analysis and risk evaluation techniques have developed to the point where quantitatively meaningful risks can be calculated for processes and plants. However, the results are typically presented in semi-quantitative "ranked list" or "categorical matrix" formats, which are certainly useful but not optimal for making business decisions. A relatively new technique for performing valuation under uncertainty, value at risk (VaR), has been developed in the financial world. VaR is a method of evaluating the probability of a gain or loss by a complex venture, by examining the stochastic behavior of its components. We believe that combining quantitative risk assessment techniques with VaR concepts will bridge the gap between engineers and scientists who determine process risk and business leaders and policy makers who evaluate, manage, or regulate risk. We present a few basic examples of the application of VaR to hazard analysis in the chemical process industry.     

Evaluation of a decision support system for the useful application of hazardous wastes with means of immobilisation-techniques

In the Netherlands, dumping of hazardous wastes on a landfill is discouraged. On the other hand, the Building Material Decree set standards to building materials in order to protect surface-, groundwater and soil from the leaching of hazardous components. Moreover, the government intends to minimise the use of primary materials. Therefore, new applications of hazardous wastes are needed. The most promising is Stabilisation/Solidification, sometimes called immobilisation.Immobilisation-techniques are defined as changing the physical and chemical state of hazardous wastes in order to reduce the leaching of hazardous components. Despite financial incentives, few applications of immobilised wastes are known. Therefore, a Decision Support System (DSS) is necessary to calculate the impact of the immobilised waste on the environment. A DSS is developed and evaluated for a case with contaminated soil and residues from inorganic industry.The first criterion of the DSS is calledlong term behaviour and aims at minimising the release of hazardous compounds in relation to external influences and material properties. The second criterion,environmental load focuses at consumption of (non)renewable natural resources. The third criterion isfinancial consequences, which calculates the overall costs and incomes during the life cycle with respect to all stakeholders.     

Risk-based maintenance of ethylene oxide production facilities

This paper discusses a methodology for the design of an optimum inspection and maintenance program. The methodology, called risk-based maintenance (RBM) is based on integrating a reliability approach and a risk assessment strategy to obtain an optimum maintenance schedule. First, the likely equipment failure scenarios are formulated. Out of many likely failure scenarios, the ones, which are most probable, are subjected to a detailed study. Detailed consequence analysis is done for the selected scenarios. Subsequently, these failure scenarios are subjected to a fault tree analysis to determine their probabilities. Finally, risk is computed by combining the results of the consequence and the probability analyses. The calculated risk is compared against known acceptable criteria. The frequencies of the maintenance tasks are obtained by minimizing the estimated risk. A case study involving an ethylene oxide production facility is presented. Out of the five most hazardous units considered, the pipeline used for the transportation of the ethylene is found to have the highest risk. Using available failure data and a lognormal reliability distribution function human health risk factors are calculated. Both societal risk factors and individual risk factors exceeded the acceptable risk criteria. To determine an optimal maintenance interval, a reverse fault tree analysis was used. The maintenance interval was determined such that the original high risk is brought down to an acceptable level. A sensitivity analysis is also undertaken to study the impact of changing the distribution of the reliability model as well as the error in the distribution parameters on the maintenance interval.     

Modified failure mode and effects analysis using approximate reasoning

The marine industry is recognising the powerful techniques that can be used to perform risk analysis of marine systems. One technique that has been applied in both national and international marine regulations and operations is failure mode and effects analysis (FMEA). This risk analysis tool assumes a failure mode, which occurs in a system/component through some failure mechanism; the effect of this failure is then evaluated. A risk ranking is produced in order to prioritise the attention for each of the failure modes identified. The traditional method utilises the risk priority number (RPN) ranking system. This method determines the RPN by finding the multiplication of factor scores. The three factors considered are probability of failure, severity and detectability. Traditional FMEA has been criticised to have several drawbacks. These drawbacks are addressed in this paper. A new proposed approach, which utilises the fuzzy rules base and grey relation theory is presented.     

Cross-analysis of hazmat road accidents using multiple databases

Road selection for hazardous materials transportation relies heavily on risk analysis. With risk being generally expressed as a product of the probability of occurrence and the expected consequence, one will understand that risk analysis is data intensive. However, various authors have noticed the lack of statistical reliability of hazmat accident databases due to the systematic underreporting of such events. Also, official accident databases alone are not always providing all the information required (economical impact, road conditions, etc.). In this paper, we attempt to integrate many data sources to analyze hazmat accidents in the province of Quebec, Canada. Databases on dangerous goods accidents, road accidents and work accidents were cross-analyzed. Results show that accidents can hardly be matched and that these databases suffer from underreporting. Police records seem to have better coverage than official records maintained by hazmat authorities. Serious accidents are missing from government's official databases (some involving deaths or major spills) even though their declaration is mandatory.     

Historical perspective on failure rates for US commercial reactor components

To support the development of probabilistic risk assessments of US commercial nuclear power plants, significant effort has been expended to develop generic failure rates for components. Generic failure rates indicate industry-average performance of components, rather than component performance at a specific plant. Most publicly available, generic failure rate databases are typically based on data collected in the 1970s and 1980s for US nuclear power plants. Recent data analysis programs sponsored by the US Nuclear Regulatory Commission and data collection programs sponsored by the Institute of Nuclear Power Operations provide an opportunity to compare more recent failure rate estimates with those obtained in the 1970s and 1980s. These recent results indicate that many component generic failure rates are now lower than observed in the 1970s and 1980s. Suggestions for up-to-date failure rates are presented. Also, failure to run rates for standby components are presented for both short- and longer-term run times.     

Treatment and disposal of hazardous wastes in Western Europe

In western Europe, as in other industrialised areas, there has been growing concern about the disposal of wastes of a hazardous or toxic nature. The increasing quantities and complexities of wastes from industrial processes, and the greater awareness of potential risks to health of present and future generations arising from indiscriminate or inadequate methods of disposal, are causing governments to undertake an intensive examination of the whole field of waste management.Reliable data on the types and quantities of hazardous wastes are very difficult to acquire and information available is generally based on estimates.Legislative and administrative measures are being proposed and developed, which will provide a framework for better control and improved standards for the handling, treatment and disposal of toxic and other hazardous wastes.In planning disposal systems, more attention will be given to methods of recovering and recycling materials which are becoming scarce or expensive. As stricter environmental controls raise disposal costs, there will be more incentive on industry to recycle wastes, where practicable.     

Work-related maritime fatalities

All maritime fatalities investigated by Coroners that occurred in Australia from 1992 to 1998 inclusive have been collated, coded and recorded in the Australian Boating Injury Database: Fatal Injury (ABID:FI). This article focuses on the work-related maritime fatalities recorded in the database. Over the period 1992-1998 there were 74 fatalities involving people who were working for income at the time of the incident: 46 commercial fishermen, 12 seamen involved in the transport of cargo and 16 miscellaneous workers. The fatality rate of commercial fishermen has declined substantially in Australia over recent years. The main contributing factors were: hazardous conditions; an error of judgement; unsafe work practices; and failure to wear a personal flotation device (PFD) in circumstances where, in the opinion of the Coroners, it would have saved life. Hazardous conditions were much more of a factor in fishermen deaths than in other maritime deaths. Most vessels involved had an insufficient number of PFDs for the number of crew on board. The Australian fatal injury database should be updated with the details of recent fatalities in order to further monitor safety performance, causal factors and prevention measures in the maritime industry in Australia. Attention should be focused on reducing alcohol use and increasing PFD availability and usage. In order to continue to improve safety, it is essential that a constructive dialogue is maintained with industry sources, informed by independent research and up-to-date information.